Tobacco equipment inspection method, electronic equipment and program product

Abstract

The invention provides a tobacco equipment inspection method, electronic equipment and a program product, and relates to the technical field of equipment operation and maintenance management. The method comprises the following steps: acquiring operation parameters representing the operation state of to-be-tested tobacco equipment, wherein the operation parameters comprise operation indexes corresponding to a plurality of parts forming the to-be-tested tobacco equipment; according to a preset rated life cycle of the to-be-tested tobacco equipment and environment humidity and operation duration in the operation parameters, determining a weight matrix representing influence degrees of different operation indexes on the health state of the to-be-tested tobacco equipment; according to the operation parameters and the weight matrix, evaluating the health state of the to-be-tested tobacco equipment to obtain an evaluation result; and determining an inspection strategy of the tobacco equipment to be detected according to the evaluation result. In this way, the problems that a traditional tobacco equipment operation and maintenance management mode is too high in labor cost, and human subjective equipment health state assessment has no quantitative index, so that the cost is high, and the assessment effect is unstable are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment operation and maintenance management, and in particular to a tobacco equipment inspection method, electronic equipment, and program product. Background Art

[0002] With the development of science and technology, current production operations are no longer limited to traditional manual monitoring and operation. Automated operations and operation and maintenance management are the mainstream technical means and goals of current producers in production operations.

[0003] In the existing tobacco production equipment management, the operation and maintenance management of the equipment mainly relies on manual recording of equipment operation data and evaluating the health status of the equipment based on the equipment's historical operation data, so as to promptly remind relevant personnel to maintain the equipment when the equipment health status is poor and there may be a risk of production failure.

[0004] Therefore, the labor cost of traditional tobacco equipment operation and maintenance management methods is too high, and the subjective equipment health status assessment has no quantitative indicators, resulting in high costs and unstable assessment results. Summary of the Invention

[0005] In view of this, the purpose of the embodiments of the present application is to provide a tobacco equipment inspection method, electronic equipment and program product, which can improve the traditional tobacco equipment operation and maintenance management method, which has high labor costs and subjective equipment health status assessment without quantitative indicators, resulting in high costs and unstable evaluation results.

[0006] To achieve the above technical objectives, the technical solutions adopted in this application are as follows:

[0007] In a first aspect, an embodiment of the present application provides a tobacco equipment inspection method, the method comprising:

[0008] Acquiring operating parameters representing an operating state of the tobacco device to be tested, wherein the operating parameters include operating indicators corresponding to a plurality of components constituting the tobacco device to be tested;

[0009] Determining a weight matrix representing the degree of influence of different operating indicators on the health status of the tobacco device to be tested based on a preset rated life cycle of the tobacco device to be tested and the ambient humidity and operating time in the operating parameters;

[0010] Evaluate the health status of the tobacco device to be tested according to the operating parameters and the weight matrix to obtain an evaluation result;

[0011] An inspection strategy for the tobacco equipment to be tested is determined based on the evaluation result.

[0012] In conjunction with the first aspect, in some optional embodiments, between obtaining operating parameters representing the operating state of the tobacco device to be tested and determining a weight matrix representing the degree of influence of different operating indicators on the health state of the tobacco device to be tested based on a preset rated life cycle of the tobacco device to be tested and the ambient humidity and operating time in the operating parameters, the method further includes:

[0013] The operating parameters are normalized to obtain a normalized feature vector:

[0014]

[0015] Where, represents the normalized eigenvector corresponding to the jth operating indicator, Indicates the operating parameters corresponding to the jth operating index, μ j represents the average value of the historical data of the jth operating indicator, σ j Indicates the standard deviation of the historical data of the j-th operating indicator;

[0016] Evaluate the health status of the tobacco device to be tested according to the operating parameters and the weight matrix to obtain an evaluation result, including:

[0017] The health status of the tobacco device to be tested is evaluated according to the normalized eigenvector and the weight matrix to obtain the evaluation result.

[0018] In conjunction with the first aspect, in some optional embodiments, a weight matrix representing the degree of influence of different operating indicators on the health status of the tobacco device to be tested is determined based on the preset rated life cycle of the tobacco device to be tested and the ambient humidity and operating time in the operating parameters, including:

[0019] The weight matrix is ​​determined according to the preset rated life cycle of the tobacco device to be tested, the ambient humidity, and the operating time:

[0020]

[0021] Where w j represents the jth element in the weight matrix, represents the preset basic failure weight corresponding to the jth operating indicator, RH represents the ambient humidity, α j represents the aging nonlinear coefficient corresponding to the jth operating indicator, t represents the operating time, Represents the preset rated life cycle corresponding to the jth operating indicator.

[0022] In conjunction with the first aspect, in some optional implementations, evaluating the health status of the tobacco device to be tested based on the normalized eigenvector and the weight matrix to obtain the evaluation result includes:

[0023] Obtaining a preset engineering safety threshold corresponding to each component of the tobacco equipment to be tested;

[0024] Determine, based on the normalized eigenvector, the weight matrix, and the preset engineering safety threshold, a health index representing the health status of the tobacco equipment to be tested as the evaluation result:

[0025]

[0026] Where HI represents the health index, w j represents the jth element in the weight matrix, L j Represents the preset engineering safety threshold corresponding to the j-th component of the tobacco equipment under test.

[0027] In conjunction with the first aspect, in some optional implementations, determining an inspection strategy for the tobacco equipment to be tested based on the evaluation result includes:

[0028] According to the evaluation result, an inspection cycle of the tobacco equipment to be tested is determined as the inspection strategy:

[0029]

[0030] Where, T next represents the inspection cycle, HI represents the health index in the evaluation result, D represents the basic cycle, and I∈[0,1] represents the production plan intensity.

[0031] In conjunction with the first aspect, in some optional implementations, the method further includes:

[0032] According to the evaluation result, a preset fault diagnosis strategy is used to predict the fault type of the tobacco equipment to be tested, and a prediction result is obtained.

[0033] In conjunction with the first aspect, in some optional implementations, based on the evaluation result, a fault type of the tobacco device to be tested is predicted by a preset fault diagnosis strategy to obtain a prediction result, including:

[0034] When the health index in the evaluation result is less than a preset threshold, the abnormal features of the tobacco device to be tested are extracted according to the normalized feature vector and the preset engineering safety threshold:

[0035]

[0036] Where, X abnormalIndicates abnormal characteristics;

[0037] Predicting the probability of different fault types existing in the tobacco device to be tested based on the abnormal characteristics;

[0038] The fault type corresponding to the maximum value of the probability is determined as the prediction result.

[0039] In conjunction with the first aspect, in some optional implementations, predicting the probability of different fault types in the tobacco device to be tested based on the abnormal characteristics includes:

[0040] Obtaining a conditional probability of occurrence of the abnormal feature under the different fault types;

[0041] Obtaining a priori probabilities representing the frequencies of occurrence of the different fault types in the historical operation of the tobacco equipment to be tested;

[0042] Based on the conditional probability and the prior probability, the probability of different fault types occurring in the tobacco device under test under the abnormal characteristics is predicted:

[0043]

[0044] Where, P(X abnormal |F i ) represents the conditional probability, P prior (F i ) represents the prior probability, and n represents the number of fault types.

[0045] In a second aspect, an embodiment of the present application further provides an electronic device, comprising a processor and a memory coupled to each other, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the electronic device executes the above-mentioned method.

[0046] In a third aspect, an embodiment of the present application further provides a computer program product, comprising a computer program, which implements the above method when executed by a processor.

[0047] The invention adopting the above technical solution has the following advantages:

[0048] In the technical solution provided by this application, operating parameters, including multiple operating indicators, are first obtained. Based on the preset rated life cycle of the tobacco equipment under test, as well as the ambient humidity and operating time within the operating parameters, a weight matrix is ​​determined to characterize the degree of influence of different operating indicators on the health status of the tobacco equipment under test. Then, based on the operating parameters and the weight matrix, the health status of the tobacco equipment under test is evaluated to obtain an evaluation result. Finally, based on the evaluation result, an inspection strategy for the tobacco equipment under test is determined. In this way, by automatically detecting the operating status of the tobacco equipment and automatically formulating an adaptive inspection strategy based on the operating status, the manual procedures required for tobacco equipment inspection are optimized. Furthermore, through standardized equipment health status assessment operations, the health indicators of the tobacco equipment are quantified, providing objective data for the formulation of tobacco equipment inspection strategies, thereby achieving the goal of improving the high cost and unstable equipment health status assessment results of traditional tobacco equipment operation and maintenance management methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present application may be further illustrated by the non-limiting embodiments provided in the accompanying drawings. It should be understood that the following drawings illustrate only certain embodiments of the present application and are therefore not to be construed as limiting the scope of the present application. It is understood that a person skilled in the art can derive other relevant drawings from these drawings without inventive effort.

[0050] Figure 1 This is a structural block diagram of the electronic device provided in an embodiment of the present application.

[0051] Figure 2 A flowchart of the tobacco equipment inspection method provided in an embodiment of the present application.

[0052] Icon: 100-electronic device; 101-processor; 102-memory. DETAILED DESCRIPTION

[0053] The present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that similar or identical parts in the drawings or descriptions are numbered the same. Implementations not shown or described in the drawings are known to those of ordinary skill in the art. In the description of this application, the terms "first," "second," etc. are used solely to distinguish descriptions and are not to be construed as indicating or implying relative importance.

[0054] Please refer to Figure 1 In an embodiment of the present application, an electronic device 100 may include a processor 101 and a memory 102. The memory 102 stores a computer program, and when the computer program is executed by the processor 101, the electronic device 100 can perform the corresponding steps in the following tobacco equipment inspection method.

[0055] In this embodiment, the processor 101 may be an integrated circuit chip having signal processing capabilities. The processor 101 may be a general-purpose processor. For example, the processor 101 may be a central processing unit (CPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present application.

[0056] The memory 102 may be, but is not limited to, a random access memory, a read-only memory, a programmable read-only memory, an erasable programmable read-only memory, an electrically erasable programmable read-only memory, etc. In this embodiment, the memory 102 may be used to store operating parameters, a preset rated life cycle, a weight matrix, an evaluation result inspection strategy, a preset fault diagnosis strategy, prediction results, etc. Of course, the memory 102 may also be used to store programs, and the processor 101 executes the program after receiving an execution instruction.

[0057] In this embodiment, the electronic device 100 may be a personal computer, a laptop computer, a cloud server, a controller connected to tobacco production equipment, etc. In this embodiment, the electronic device 100 takes a personal computer as an example, and the electronic device 100 also includes a mobile terminal connected to the personal computer, so that when a user conducts tobacco equipment inspections, the user can use the mobile terminal to read an NFC (Near Field Communication) card installed on the tobacco equipment to be tested, and then write or read the operating parameters of the tobacco equipment to be tested.

[0058] In this embodiment, the electronic device 100 can be used to obtain operating parameters including multiple operating indicators and, based on the preset rated life cycle of the tobacco device under test and the ambient humidity and operating time within the operating parameters, determine a weight matrix representing the degree to which the different operating indicators affect the health status of the tobacco device under test. The health status of the tobacco device under test is then evaluated based on the operating parameters and the weight matrix to obtain an evaluation result. Finally, an inspection strategy for the tobacco device under test is determined based on the evaluation result.

[0059] It is understandable that Figure 1 The structure of the electronic device 100 shown in FIG is only a schematic diagram of a structure. The electronic device 100 may also include Figure 1 More components shown. Figure 1 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0060] Please refer to Figure 2 The present application also provides a tobacco equipment inspection method, which can be applied to the electronic device 100, and the electronic device 100 executes or implements each step of the method. The tobacco equipment inspection method can include the following steps:

[0061] Step 210, obtaining operating parameters representing the operating state of the tobacco device to be tested, wherein the operating parameters include operating indicators corresponding to a plurality of components constituting the tobacco device to be tested;

[0062] Step 220 , determining a weight matrix representing the degree of influence of different operating indicators on the health status of the tobacco device to be tested based on the preset rated life cycle of the tobacco device to be tested and the ambient humidity and operating time in the operating parameters;

[0063] Step 230: Evaluate the health status of the tobacco device to be tested based on the operating parameters and the weight matrix to obtain an evaluation result;

[0064] Step 240: Determine an inspection strategy for the tobacco equipment to be tested based on the evaluation result.

[0065] In the above-described embodiment, operating parameters, including multiple operating indicators, are first acquired. Based on the preset rated life cycle of the tobacco equipment under test, as well as the ambient humidity and operating time within the operating parameters, a weight matrix is ​​determined to characterize the degree to which the different operating indicators affect the health status of the tobacco equipment under test. Then, based on the operating parameters and the weight matrix, the health status of the tobacco equipment under test is evaluated to obtain an evaluation result. Finally, an inspection strategy for the tobacco equipment under test is determined based on the evaluation result. In this manner, by automatically detecting the operating status of the tobacco equipment and automatically formulating an adaptive inspection strategy based on the operating status, the manual procedures required for tobacco equipment inspections are optimized. Furthermore, through standardized equipment health status assessment operations, the health indicators of the tobacco equipment are quantified, providing objective data for the formulation of tobacco equipment inspection strategies. This improves the high cost and unstable equipment health status assessment results of traditional tobacco equipment operation and maintenance management methods.

[0066] The following is a detailed description of the steps of the tobacco equipment inspection method:

[0067] In step 210, the acquisition of operating parameters can be that the user reads the NFC card set on the tobacco device to be tested through a mobile terminal (such as a mobile phone, tablet computer, etc.), and then writes the operating indicators of each component of the tobacco device to be tested measured by the user into the back-end database through the mobile terminal, and stores them in the memory 102 of the above-mentioned electronic device 100, so as to facilitate the subsequent inspection strategy formulation, based on the instructions issued by the user through the processor 101 of the electronic device 100 to call; or, the acquisition of operating parameters can also be that the operating indicators of each component are sensed by a sensor embedded in the tobacco device to be tested, and are written to the NFC card set on the tobacco device to be tested based on a certain frequency (for example, once every ten minutes, once every half an hour, once an hour, etc.), and then when the user holds the mobile terminal to read the NFC card, the operating indicator data of each component is imported into the back-end database and stored in the memory 102 of the electronic device 100, so as to facilitate the subsequent inspection strategy formulation process, based on the instructions initiated by the user through the processor 101 to call.

[0068] In this embodiment, taking the YJ212 cigarette making unit as an example, the operating indicators in the operating parameters may include but are not limited to the vibration speed of the cutter head, the temperature rise of the drive shaft, the negative pressure sealing pressure, the lubrication flow, the operating time of the cigarette making unit, the ambient humidity of the cigarette making unit, etc.

[0069] Between step 210 and step 220, the method may further include:

[0070] The operating parameters are normalized to obtain a normalized feature vector:

[0071]

[0072] Where, Represents the normalized eigenvector corresponding to the jth operating indicator, where the normalized eigenvector refers to the set matrix of all normalized operating indicators. The normalized data corresponding to each operating indicator is a matrix element in the normalized eigenvector and can be called normalized feature data. represents the operating parameter corresponding to the jth operating indicator, μ j Represents the average value of the historical data of the jth operating indicator to eliminate the dimension effect, σ j Indicates the standard deviation of the historical data of the j-th operating indicator, which is used to characterize the degree of data dispersion;

[0073] For example, the operating indicators and their means and standard deviations may be shown in the following parameter table:

[0074] index physical quantity mean Standard deviation source 1 Cutter head vibration speed 2.3mm / s 0.45mm / s GB / T 19873.2-2023 2 Drive shaft temperature rise 28℃ 4.2℃ Equipment historical data (12 months) 3 Negative sealing pressure -0.075MPa 0.008MPa YJ212 Technical Manual Section 5.7 4 Lubrication flow 12.1L / h 0.35L / h Lubricant supplier test report

[0075] In this way, the sensor zero drift error is eliminated by the numerator term in the normalization formula of the operating parameters, and the denominator term is used to ensure that the normalized data conforms to the standard normal distribution.

[0076] In step 220, based on the preset rated life cycle of the tobacco device to be tested and the ambient humidity and operating time in the operating parameters, a weight matrix representing the degree of influence of different operating indicators on the health status of the tobacco device to be tested is determined, including:

[0077] The weight matrix is ​​determined according to the preset rated life cycle of the tobacco device to be tested, the ambient humidity, and the operating time:

[0078]

[0079] Where w j represents the jth element in the weight matrix, represents the preset basic failure weight corresponding to the jth operating indicator, RH represents the ambient humidity, and 0.02·RH is used as a temperature compensation factor to suppress the electrical parameter drift caused by high humidity. j represents the aging nonlinear coefficient corresponding to the jth operating indicator, t represents the operating time, represents the preset rated life cycle corresponding to the jth operating indicator;

[0080] In this embodiment, j can represent the number of components in the tobacco device under test. Each component corresponds to an operating indicator and its weight, which is an element in the weight matrix. The components in this embodiment may include, but are not limited to, blade vibration, negative pressure seals, drive shafts, and lubricating oil, i.e., j = 1, 2, 3, 4. In this embodiment, the preset basic failure weight represents the probability of failure of the component and is determined by FMEA (Failure Mode and Effect Analysis) analysis. The ambient humidity can be the real-time humidity of the environment in which the tobacco device under test is located, or it can be the average humidity of the tobacco device under test within a period of time before the current moment (flexibly set according to user needs, such as the week before the current moment, the three days before the current moment, the day before the current moment, etc.). The preset rated life cycle is the factory calibration data of the component, representing the service life of the component and determined by the fatigue properties of the component's material.

[0081] In this way, this embodiment improves the adaptability of the technical solution to complex working conditions and abnormal states by dynamically adjusting the weights of different fault modes, thereby improving the accuracy and robustness of subsequent health status assessment and fault diagnosis of the tobacco equipment to be tested.

[0082] In step 230, the health status of the tobacco device to be tested is evaluated based on the operating parameters and the weight matrix to obtain an evaluation result, which may include:

[0083] The health status of the tobacco device to be tested is evaluated according to the normalized eigenvector and the weight matrix to obtain the evaluation result.

[0084] Here, evaluating the health status of the tobacco device to be tested based on the normalized eigenvector and the weight matrix to obtain the evaluation result may include:

[0085] Obtaining a preset engineering safety threshold corresponding to each component of the tobacco equipment to be tested;

[0086] Determine, based on the normalized eigenvector, the weight matrix, and the preset engineering safety threshold, a health index representing the health status of the tobacco equipment to be tested as the evaluation result:

[0087]

[0088] Where HI represents the health index, w j represents the jth element in the weight matrix, L j Represents the preset engineering safety threshold corresponding to the j-th component of the tobacco equipment under test.

[0089] In this embodiment, the preset engineering safety threshold represents the boundary value of the normal working state of the corresponding component. When the normalized characteristic data of a component is greater than the preset engineering safety threshold of the component, its health will drop rapidly. j It represents the health status score function of the j-th component. It can be seen from the piecewise function that before the normalized characteristic data of the component reaches the preset engineering safety threshold, the health status of the component decays quadratically. After the normalized characteristic data of the component reaches the preset engineering safety threshold, the health status of the component decays exponentially.

[0090] In this embodiment, the preset engineering safety threshold can be calibrated through previous related experiments. The preset engineering safety threshold in this embodiment may include a cutter head vibration speed of 3.5 mm / s, a rotating shaft temperature rise of 35°C, a negative pressure sealing pressure of -0.08 MPa, and a lubrication flow rate of 11.5 L / h.

[0091] In this way, this embodiment uses piecewise functions to accurately characterize the health status attenuation trajectory of components from slight degradation to critical failure, avoiding the problem of single-aspect evaluation being insensitive to early abnormalities or missing late faults. At the same time, the weighted summation mechanism highlights the contribution weights of key components and improves the sensitivity of the overall health status assessment.

[0092] In step 240, determining an inspection strategy for the tobacco equipment to be tested based on the evaluation result may include:

[0093] According to the evaluation result, an inspection cycle of the tobacco equipment to be tested is determined as the inspection strategy:

[0094]

[0095] Where, T next represents the inspection cycle, HI represents the health index in the evaluation result, D represents the basic cycle, and I∈[0,1] represents the production plan intensity.

[0096] In this way, the inspection cycle is dynamically calculated based on the health index, and the equipment health status is divided into three intervals according to the health index (the three intervals in this embodiment are healthy, sub-healthy, and high-risk intervals as examples). As can be seen from the above inspection cycle formula, when the equipment is in a healthy state, redundant inspections are minimized within the upper limit of the cycle of 24 hours; when the equipment is in a high-risk state, high-frequency inspections are forced (with a lower limit of two hours); when the equipment is in a sub-healthy state, the production plan intensity factor I∈[0,1] (the interval 0 to 1 indicates that the production plan changes from no production to full-load production) is used to achieve coordinated optimization of operation and maintenance and production. In this way, through the health index and the production plan intensity factor, dynamic planning of the inspection cycle is achieved, inspection indicators are quantified, the objectivity of the inspection strategy is guaranteed, and inspection efficiency is improved.

[0097] As an optional implementation, the method may further include:

[0098] According to the evaluation result, a preset fault diagnosis strategy is used to predict the fault type of the tobacco equipment to be tested, and a prediction result is obtained.

[0099] In this embodiment, based on the evaluation result, a preset fault diagnosis strategy is used to predict the fault type of the tobacco device to be tested, and the prediction result is obtained, which may include:

[0100] When the health index in the evaluation result is less than a preset threshold, the abnormal features of the tobacco device to be tested are extracted according to the normalized feature vector and the preset engineering safety threshold:

[0101]

[0102] Where, X abnormal Indicates abnormal characteristics;

[0103] Predicting the probability of different fault types existing in the tobacco device to be tested based on the abnormal characteristics;

[0104] The fault type corresponding to the maximum value of the probability is determined as the prediction result.

[0105] In this embodiment, by converting the abstract health index into an interpretable component-level abnormality ratio parameter (for example, the vibration speed of the cutter head exceeds the standard by 1.2 times), operation and maintenance personnel are assisted in quickly locating the problem component. At the same time, the maximum probability principle is adopted to simplify the fault type judgment logic and reduce the decision-making complexity in multi-classification scenarios.

[0106] In this embodiment, predicting the probability of different fault types in the tobacco device to be tested based on the abnormal characteristics may include:

[0107] Obtaining a conditional probability of occurrence of the abnormal feature under the different fault types;

[0108] Obtaining a priori probabilities representing the frequencies of occurrence of the different fault types in the historical operation of the tobacco equipment to be tested;

[0109] Based on the conditional probability and the prior probability, the probability of different fault types occurring in the tobacco device under test under the abnormal characteristics is predicted:

[0110]

[0111] Where, P(X abnormal |F i ) represents the conditional probability, P prior (F i ) represents the prior probability, and n represents the number of fault types.

[0112] In this embodiment, F i Indicates fault codes of different fault types. The various parameters in this embodiment can be represented by the following fault mode examples:

[0113] <![CDATA[Fault code F i > Fault type <![CDATA[P prior (F i )]]> F001 Cutter head bearing wear 0.32 F005 Negative pressure fan failure 0.18 F012 Lubrication line blocked 0.25

[0114] In this example, the Bayesian theorem is used to calculate the probability of different types of failures. Probabilistic calculations quantify the uncertainty of different failures. Using prior and conditional probabilities, the prediction results are refined by integrating historical device performance patterns with real-time data, thus avoiding the risk of misjudgment from a single data source. For example, this distinguishes between occasional sensor anomalies and actual mechanical failures, improving the reliability of prediction results.

[0115] It should be noted that those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the electronic device 100 described above can refer to the corresponding processes of each step in the aforementioned method, and will not be elaborated here.

[0116] An embodiment of the present application further provides a computer program product, including a computer program, which implements the above-mentioned tobacco equipment inspection method when executed by the processor 101.

[0117] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present application can be implemented through hardware or by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present application.

[0118] In summary, the embodiments of the present application provide a tobacco equipment inspection method, an electronic device 100, and a program product. In this technical solution, first, operating parameters including multiple operating indicators are obtained, and based on the preset rated life cycle of the tobacco equipment to be tested and the ambient humidity and operating time in the operating parameters, a weight matrix representing the degree of influence of different operating indicators on the health status of the tobacco equipment to be tested is determined; then, based on the operating parameters and the weight matrix, the health status of the tobacco equipment to be tested is evaluated to obtain an evaluation result; finally, based on the evaluation result, an inspection strategy for the tobacco equipment to be tested is determined. In this way, by automatically detecting the operating status of the tobacco equipment and automatically formulating an adaptive inspection strategy based on the operating status, the manual procedures required for tobacco equipment inspection are optimized. In addition, through standardized equipment health status evaluation operations, the health indicators of the tobacco equipment are quantified, providing objective data for the formulation of tobacco equipment inspection strategies, thereby achieving the purpose of improving the high cost of traditional tobacco equipment operation and maintenance management methods and the unstable equipment health status evaluation results.

[0119] In the embodiments provided in the present application, it should be understood that the disclosed method can also be implemented in other ways. The method embodiments described above are merely schematic. For example, the flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the methods and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of code, and a part of the module, program segment or code includes one or more executable instructions for implementing the specified logical function. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. In addition, the functional modules in the various embodiments of the present application can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0120] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A tobacco equipment inspection method, characterized in that: The method comprises: Acquiring operating parameters representing an operating state of the tobacco device to be tested, wherein the operating parameters include operating indicators corresponding to a plurality of components constituting the tobacco device to be tested; Determining a weight matrix representing the degree of influence of different operating indicators on the health status of the tobacco device to be tested based on a preset rated life cycle of the tobacco device to be tested and the ambient humidity and operating time in the operating parameters; Evaluate the health status of the tobacco device to be tested according to the operating parameters and the weight matrix to obtain an evaluation result; An inspection strategy for the tobacco equipment to be tested is determined based on the evaluation result.

2. The method according to claim 1, characterized in that Between obtaining operating parameters representing the operating state of the tobacco device to be tested and determining a weight matrix representing the degree of influence of different operating indicators on the health state of the tobacco device to be tested based on a preset rated life cycle of the tobacco device to be tested and the ambient humidity and operating time in the operating parameters, the method further includes: The operating parameters are normalized to obtain a normalized feature vector: Where, represents the normalized eigenvector corresponding to the jth operating indicator, Indicates the operating parameters corresponding to the jth operating index, μ j represents the average value of the historical data of the jth operating indicator, σ j Indicates the standard deviation of the historical data of the j-th operating indicator; Evaluate the health status of the tobacco device to be tested according to the operating parameters and the weight matrix to obtain an evaluation result, including: The health status of the tobacco device to be tested is evaluated according to the normalized eigenvector and the weight matrix to obtain the evaluation result.

3. The method according to claim 1, characterized in that Determining a weight matrix representing the degree of influence of different operating indicators on the health status of the tobacco device to be tested based on the preset rated life cycle of the tobacco device to be tested and the ambient humidity and operating time in the operating parameters, including: The weight matrix is ​​determined according to the preset rated life cycle of the tobacco device to be tested, the ambient humidity, and the operating time: Where w j represents the jth element in the weight matrix, represents the preset basic failure weight corresponding to the jth operating indicator, RH represents the ambient humidity, α j represents the aging nonlinear coefficient corresponding to the jth operating indicator, t represents the operating time, Represents the preset rated life cycle corresponding to the jth operating indicator.

4. The method according to claim 2, characterized in that Evaluating the health status of the tobacco device to be tested according to the normalized eigenvector and the weight matrix to obtain the evaluation result includes: Obtaining a preset engineering safety threshold corresponding to each component of the tobacco equipment to be tested; Determine, based on the normalized eigenvector, the weight matrix, and the preset engineering safety threshold, a health index representing the health status of the tobacco equipment to be tested as the evaluation result: Where HI represents the health index, w j represents the jth element in the weight matrix, L j Represents the preset engineering safety threshold corresponding to the j-th component of the tobacco equipment under test.

5. The method according to claim 1, wherein Determining an inspection strategy for the tobacco equipment to be tested based on the evaluation results includes: According to the evaluation result, an inspection cycle of the tobacco equipment to be tested is determined as the inspection strategy: Where, T next represents the inspection cycle, HI represents the health index in the evaluation result, D represents the basic cycle, and I∈[0,1] represents the production plan intensity.

6. The method according to claim 4, characterized in that The method further comprises: According to the evaluation result, a preset fault diagnosis strategy is used to predict the fault type of the tobacco equipment to be tested, and a prediction result is obtained.

7. The method according to claim 6, characterized in that According to the evaluation results, a fault type of the tobacco device to be tested is predicted by a preset fault diagnosis strategy to obtain a prediction result, including: When the health index in the evaluation result is less than a preset threshold, the abnormal features of the tobacco device to be tested are extracted according to the normalized feature vector and the preset engineering safety threshold: Where, X abnormal Indicates abnormal characteristics; Predicting the probability of different fault types existing in the tobacco device to be tested based on the abnormal characteristics; The fault type corresponding to the maximum value of the probability is determined as the prediction result.

8. The method according to claim 7, characterized in that Predicting the probability of different fault types in the tobacco device under test based on the abnormal characteristics includes: Obtaining a conditional probability of occurrence of the abnormal feature under the different fault types; Obtaining a priori probabilities representing the frequencies of occurrence of the different fault types in the historical operation of the tobacco equipment to be tested; Based on the conditional probability and the prior probability, the probability of different fault types occurring in the tobacco device under test under the abnormal characteristics is predicted: Where, P(X abnormal |F i ) represents the conditional probability, P prior (F i ) represents the prior probability, and n represents the number of fault types.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory coupled to each other, wherein a computer program is stored in the memory. When the computer program is executed by the processor, the electronic device executes the method according to any one of claims 1 to 8.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 8.

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